Visualization

[wizenink]

No description provided.

[gemini-code-assist]

Summary of Changes

Hello @wizenink, I'm Gemini Code Assist¹! I'm currently reviewing this pull request and will post my feedback shortly. In the meantime, here's a summary to help you and other reviewers quickly get up to speed!

This pull request significantly enhances the stft-rs crate by introducing a powerful new visualization feature. Users can now easily generate high-quality spectrogram images from their processed audio data, providing a clear visual representation of frequency content over time. This addition makes the crate more versatile for audio analysis, research, and educational purposes.

Highlights

• New Visualization Feature: Introduced a new visualization feature that allows for generating image representations of spectrograms. This feature is opt-in and can be enabled via cargo run --example visualization --features visualization.
• Spectrogram Image Generation: Added functionality to convert Spectrum data into image files (e.g., PNG) with customizable settings such as color maps (Viridis, Magma, Inferno, Plasma, Grayscale), output dimensions, and decibel range for color mapping.
• New Example: A new example (examples/visualization.rs) has been added to demonstrate the usage of the visualization feature. It showcases generating spectrograms for chirp, multi-tone, and Mel-scale signals, and compares different color maps.
• Dependency Additions: New optional dependencies image and colorgrad have been added to support the image generation capabilities. This also led to numerous transitive dependency additions in Cargo.lock.

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[gemini-code-assist]

Code Review

This pull request introduces a new visualization feature to generate spectrogram images from Spectrum data. The implementation is well-structured, adding a visualization module with a SpectrumExt trait and a corresponding example. My review includes a few suggestions to improve the API consistency and fix an issue in the example code.

• In src/visualization.rs, I've suggested a change to improve type consistency for the db_range configuration, which will make the API more robust, especially for f64 data.
• In examples/visualization.rs, I've identified that the code for saving the mel spectrogram is commented out, which makes the example's output misleading. This should be addressed to ensure the example works as described.

[gemini-code-assist]

This code to save the mel spectrogram image is commented out, but the main function prints that mel_speech.png is generated. This is misleading for users running the example.

This is likely because SpectrumExt is not implemented for MelSpectrum. To fix this, you could implement the SpectrumExt trait for MelSpectrum<T>. The implementation would be slightly different as MelSpectrum can already contain dB-scaled data.

[gemini-code-assist]

For better precision and consistency, especially when dealing with f64 data, consider using (f64, f64) for db_range. This allows all intermediate decibel calculations to be done in f64 before the final normalization and conversion to color. This change will require a small adjustment in the to_image_with function.

Suggested change

	pub db_range: (f32, f32), // (min_db, max_db) for color mapping
	pub db_range: (f64, f64), // (min_db, max_db) for color mapping

[gemini-code-assist]

Following the change of db_range to (f64, f64), the explicit casts to f64 are no longer necessary here, simplifying the code.

Suggested change

	let normalized = ((db - min_db as f64) / range as f64).clamp(0.0, 1.0);
	let normalized = ((db - min_db) / range).clamp(0.0, 1.0);